Top Remote Machine Learning Jobs in San Luis Obispo, CA

Leads Propel America's product and technology strategy, including the Fellow Portal, AI integrations, technology roadmap, software development, Salesforce, infrastructure, data systems, cybersecurity, and vendor relationships. Manages technical staff and outsourced IT providers, oversees architecture, QA, releases, compliance, data privacy, and disaster recovery, and partners cross-functionally to translate organizational needs into scalable products and technology solutions.

Own the market growth strategy for Luma in biologics research, including segmentation, positioning, competitive analysis, sales enablement, AI use-case development, thought leadership, and customer adoption. Partner across Siemens, Product, Sales, Marketing, Finance, and Services to translate biologics research needs into software value, build market credibility, support strategic pursuits, and drive pipeline and wins.

Designs and builds data ingestion, feature engineering, analytics, and machine learning pipelines using healthcare and other structured or unstructured data. Develops, tunes, deploys, monitors, and documents predictive models and enterprise data products. Collaborates with data scientists, engineers, product managers, and stakeholders while ensuring data quality, reliability, and production engineering standards.

Develop, train, evaluate, deploy, and monitor machine learning and statistical models using Databricks, Python, SQL, Spark, Delta Lake, and MLflow. Prepare datasets, engineer features, manage model lifecycles, validate data, and support governance practices. Translate client requirements into scalable analytics solutions, analyze trends, and communicate findings to technical and non-technical stakeholders while collaborating across data science, engineering, cloud, security, and business teams.

Implement customer projects using Python, machine learning, and deep-learning tools for engineering, physics, CAD, CAE, and manufacturing workflows. Develop proofs of concept, analyze project data, train customer teams, and translate customer feedback into product improvements. The role requires strong engineering and machine-learning knowledge, simulation experience, customer-facing communication, and travel to US customer locations.

Leads enterprise AI architecture strategy, standards, governance, and roadmaps across products, platforms, data, and business processes. Guides solutions involving generative AI, agentic AI, RAG, machine learning, automation, cloud platforms, and AI infrastructure. Partners with executives and technical teams on architecture reviews, security, compliance, scalability, and cost optimization; mentors senior engineers and provides hands-on leadership through prototypes and critical problem resolution.

Senior Commercial Counsel will draft, review, and negotiate complex subscription, partnership, vendor, and other commercial agreements. The role primarily supports a global Sales organization, advises cross-functional teams, manages contracts managers, and handles enterprise and strategic partnership transactions. Responsibilities include balancing competing priorities, supporting legal projects, and providing practical, business-minded legal guidance in a fast-paced environment.

Own end-to-end customer deployments for an AI platform used in mining. Learn site operations, create deployment plans, manage stakeholder cadences, track risks and value, and support adoption. Build reports, dashboards, and lightweight tools using SQL, Python, or AI coding tools. Translate field observations into product requirements, support sales and account expansion, and help establish scalable deployment processes and playbooks.

Own audience or measurement products for Fetch’s monetization business, translating advertiser goals and purchase behavior into predictive models, datasets, and causal studies. Build and validate audience expansion, measure advertising outcomes, assess bias and uncertainty, and improve products using campaign results. Partner with Product, Engineering, Sales, and GTM, present findings to customers, and develop reproducible analyses and production-ready assets.

Designs, trains, evaluates, and operationalizes intelligent document-processing solutions using OCR, machine learning, LLMs, Python, and cloud data pipelines. Builds extraction, validation, reconciliation, exception-handling, and human-review workflows for sensitive information. Develops secure, auditable, configuration-driven systems with API integrations, monitoring, testing, CI/CD, and infrastructure as code. Partners with business experts to define document fields, quality thresholds, validation rules, and acceptance criteria.

Lead product vision and roadmap for data and analytics products (ML, generative AI, data pipelines, BI). Translate business needs into developer-ready features, maintain backlog, collaborate with engineering and stakeholders, track KPIs, and drive adoption and continuous improvement.

Designs and delivers integrated cloud, AI, and GPU infrastructure solutions for strategic technology partners. Responsibilities include architecting integrations, building production-grade reference implementations, defining networking and security patterns, enabling partner engineering teams, supporting customer deployments, troubleshooting complex environments, and translating partner feedback into product roadmap requirements. The role requires deep Kubernetes, Terraform, Python, AI inference, integration architecture, and cloud infrastructure expertise.

Own Pinterest’s strategy and roadmap for combating deceptive commerce content, including scams, fake storefronts, AI-generated abuse, and misleading merchant content. Define metrics, detection and enforcement approaches, and partner with Policy, Engineering, Data Science, Operations, Monetization, and Adversarial/Spam teams. Lead ML-powered detection products, manage enforcement tradeoffs, analyze adversarial dynamics, and drive cross-functional alignment to protect users while limiting false positives.

Own Pinterest’s company-wide strategy for detecting and enforcing against bots, account takeovers, spam, and other adversarial behavior. Define multi-year roadmaps, develop ML-powered detection and enforcement systems, establish measurement strategies, and coordinate investment across Policy, Operations, Engineering, Data Science, Security, and Identity teams. Lead executive alignment while balancing enforcement effectiveness with false-positive user impact.

Leads the launch of BGO’s enterprise sales motion for its AI-first data operations proposition. Responsibilities include developing prospecting strategy and sales playbooks, generating new-logo pipeline, selling complex $1M+ enterprise solutions, building executive relationships, closing transformational deals, supporting AI/ML product integration, and representing the company at industry events. The role partners with marketing, communications, client solutions, and leadership on RFPs, product roadmap development, and strategic market initiatives.

Leads a recruiter pod while personally managing quota-carrying GTM hiring across sales teams and regions. Coaches recruiters, owns hiring quality and funnel performance, partners with sales leadership, and builds an AI-forward recruiting function. The role also develops Boston’s GTM talent community through events, manages reporting and forecasting, and serves as a strategic talent partner for territories, competitors, and workforce planning.

Lead implementations of iQueue for Operating Rooms from discovery through configuration, validation, and rollout. Partner with hospital, clinical, operational, IT, and executive stakeholders to optimize OR workflows, scheduling, staffing, utilization, and access. Responsibilities include data analysis, solution design, product configuration, user acceptance testing, change management, risk monitoring, stakeholder alignment, and go-live readiness. Travel to customer sites is required up to 40–50%.

Own technical wins for strategic enterprise sales, partnering with Account Executives to discover customer needs and develop production-ready solutions. Build proofs of concept, demonstrations, prototype AI agents, and supporting tools while engaging AI teams, data platform teams, and enterprise architects. Apply hands-on experience with LLMs, agents, data science, machine learning, or data engineering to explain how agents retrieve data and use business context.

Design and implement scalable data pipelines and ML algorithms to optimize StackAdapt's digital advertising platform. Collaborate with teams to solve complex problems.

Lead technical client onboarding, migrations, solution design, integrations, data orchestration, troubleshooting, and project delivery for Movable Ink’s AI-powered personalization platform. Partner with clients and internal teams to implement custom workflows, APIs, webhooks, and data solutions. Conduct training and workshops, provide product expertise, advise on roadmap improvements, and support long-term client success across email and mobile marketing programs.

Serve as primary client contact for a portfolio of loyalty-program clients. Scope and manage end-to-end actuarial analyses rooted in predictive modeling and machine learning, validate model outputs, translate results into clear recommendations and presentations, and partner with analysts and data scientists to deliver high-quality, client-facing work in a fully remote consulting environment.

Leads cyber risk assurance strategy and multidisciplinary teams responsible for control monitoring, testing, evidence management, issue remediation, audit support, regulatory readiness, and assurance automation. The role advances continuous, AI-enabled assurance by translating regulatory and cybersecurity requirements into measurable outcomes, maintaining assurance frameworks, evaluating control effectiveness, managing concurrent activities, and reporting metrics to support executive risk decisions.

Lead technical discovery and presales engagements for Zendesk’s AI-powered CX and employee service platform. Design scalable solutions, demos, pilots, and proofs of value; integrate APIs, middleware, telephony, and cloud platforms; and translate AI capabilities into measurable business outcomes. Collaborate with Sales, Product, Engineering, and Customer Success to drive technical strategy, customer adoption, ROI measurement, and product innovation.

Analyze telematics, IoT, sensor, and firmware data to evaluate hardware performance, reliability, and field issues. Build dashboards and reports, identify trends and anomalies, apply statistical and machine learning techniques, validate firmware improvements, and provide actionable insights to engineering, product, data science, and customer support teams. Help develop scalable data pipelines and promote data-driven hardware and software development.

Own delivery of enterprise AI automation projects from planning through rollout. Manage scope, timelines, milestones, budgets, risks, dependencies, client communication, status reporting, and change orders. Coordinate cross-functional teams and stakeholders, lead project meetings, track action items through completion, support user adoption and production handoff, and identify process improvements using AI tools.